Interpretation of Resistivity Piezocone Tests in a Contaminated Municipal Solid Waste Disposal Site
Bibliographic record
Abstract
Abstract A resistivity piezocone (RCPTU–resistivity cone penetration test with pore pressure measurement) and groundwater and soil samplers were used to detect contamination from a landfill for urban solid waste located in the state of São Paulo in southeastern Brazil. Background resistivity values were obtained in the laboratory using undisturbed soil samples. The strong influence of clay minerals common in tropical soils made it difficult to interpret the tests and to differentiate potentially contaminated zones from changes in soil type. A local correlation between fines content and the soil behavior index (Ic) of the various collected soils allowed the RCPTU tests to be interpreted to identify the contaminated regions of the aquifer. These results showed excellent repeatability and allowed for a detailed stratigraphic analysis of the highly heterogeneous profiles. Electrical resistivity measurements have proven to be an interesting resource to help detect contaminated soils, thus improving the quality and efficiency of geoenvironmental site investigations using integrated direct and indirect techniques. The interpretation of resistivity piezocone tests for the study site is not straightforward as it is in sedimentary sands since soil genesis affects soil behavior and soil and water sampling is required to support interpretation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".